Paul Stapor

2018

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Paul Stapor trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Stephen G. Nash
  2. Donald Goldfarb
  3. Mark A. Girolami
  4. Andreas Wächter
  5. Richard H. Byrd
  6. Yann Dauphin
  7. Ben Calderhead
  8. Lorenz T. Biegler
  9. Jean Charles Gilbert
  10. Razvan Pascanu

Papers from Paul Stapor's perspective

Ordered by how strongly the researchers Paul Stapor trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  7. Learning Multiple Layers of Features from Tiny Images
  8. ImageNet: A large-scale hierarchical image database
  9. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers